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import numpy as np
import os
import imageio
import math
import torch
# convert a tensor into a numpy array
def tensor2im(image_tensor, bytes=255.0, imtype=np.uint8):
if image_tensor.dim() == 3:
image_numpy = image_tensor.cpu().float().numpy()
else:
image_numpy = image_tensor[0].cpu().float().numpy()
image_numpy = (np.transpose(image_numpy, (1, 2, 0)) + 1) / 2.0 * bytes
return image_numpy.astype(imtype)
# conver a tensor into a numpy array
def tensor2array(value_tensor):
if value_tensor.dim() == 3:
numpy = value_tensor.view(-1).cpu().float().numpy()
else:
numpy = value_tensor[0].view(-1).cpu().float().numpy()
return numpy
def save_image(image_numpy, image_path):
if image_numpy.shape[2] == 1:
image_numpy = image_numpy.reshape(image_numpy.shape[0], image_numpy.shape[1])
imageio.imwrite(image_path, image_numpy)
def mkdirs(paths):
if isinstance(paths, list) and not isinstance(paths, str):
for path in paths:
mkdir(path)
else:
mkdir(paths)
def mkdir(path):
if not os.path.exists(path):
os.makedirs(path)